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@ -1,4 +1,4 @@
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link_match : page link of match in Premier League Official websitemarkdow
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link_match : page link of match in Premier League Official website
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season : match season
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date : match date
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home_team : home team
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@ -1,17 +1,5 @@
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import pandas as pd
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from fuzzy import *
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def save_to_csv(filename, dataframe):
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dataframe.to_csv(filename, mode='a', index=False, header=not pd.DataFrame().append(dataframe).empty)
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def split_to_parts(dataframe, part_size):
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for i in range(0, len(dataframe), part_size):
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yield dataframe.iloc[i:i + part_size]
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def przetwarzaj_co_50_rekordow(plik_wejsciowy, plik_wyjsciowy):
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dataframe_wejsciowe = pd.read_csv(plik_wejsciowy)
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from simpful import *
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def generateTrainingData(dataframe):
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columns = ['season','date','home_team','away_team','result_full','home_passes','away_passes',
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@ -22,45 +10,25 @@ def generateTrainingData(dataframe):
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def generateFuzzyLogicData(dataframe):
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columns = ['season','date','home_team','away_team','result_full','c_home_form_5m','c_away_form_5m',#,'c_home_passes','c_away_passes',
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# 'c_home_possession','c_away_possession','c_home_shots','c_away_shots',
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'c_home_diff_5m', 'c_away_diff_5m',"c_home_form_5s",
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'c_away_form_5s','c_home_diff_5s','c_away_diff_5s'
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, 'c_home_aggression_5m',
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'c_away_aggression_5m', 'c_away_shots_5m','c_away_shots_5m',
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'c_away_shots_5btw', 'c_away_shots_5btw', 'c_away_defence_5m',
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'c_away_defence_5m', 'c_away_defence_5btw', 'c_away_defence_5btw',
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'c_home_passing_5m', 'c_away_passing_5m', 'c_home_passing_5btw',
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'c_away_passing_5btw', 'c_away_aggression_5btw', 'c_away_aggression_5btw'
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#'c_home_aggression_season', 'c_away_aggression_season',
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# 'c_home_form_season','c_away_form_season',
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# 'c_home_diff_season', 'c_away_diff_season'
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]
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'c_home_diff_5m', 'c_away_diff_5m','c_home_form_season','c_away_form_season',
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'c_home_diff_season', 'c_away_diff_season']
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return dataframe[columns]
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def last5Matches(season, teamA, data, df):
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# Wybierz rekordy dla danej pary drużyn i sezonu
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subset = df[((df['season'] == season) & ((df['home_team'] == teamA) | (df['away_team'] == teamA)))]
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# Filtruj dane, aby zawierały te przed daną datą
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before_given_date = subset[pd.to_datetime(subset['date']) < pd.to_datetime(data)]
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# Posortuj wg daty w odwrotnej kolejności
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before_given_date = before_given_date.sort_values(by='date', ascending=False)
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# Wybierz 5 ostatnich przed daną datą
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last_before_date = before_given_date.head(5)
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return last_before_date, "_5m"
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return last_before_date
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def last5MatchesBtwTeams(teamA, teamB, data, df):
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subset = df[(((df['home_team'] == teamA) | (df['away_team'] == teamA)) & ((df['home_team'] == teamB) | (df['away_team'] == teamB)))]
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before_given_date = subset[pd.to_datetime(subset['date']) < pd.to_datetime(data)]
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before_given_date = before_given_date.sort_values(by='date', ascending=False)
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last_before_date = before_given_date.head(5)
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return last_before_date, "_5btw"
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def seasonMatches(season, teamA, data, df):
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# Wybierz rekordy dla danej pary drużyn i sezonu
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@ -72,7 +40,7 @@ def seasonMatches(season, teamA, data, df):
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# Posortuj wg daty w odwrotnej kolejności
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before_given_date = before_given_date.sort_values(by='date', ascending=False)
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return before_given_date, "_s"
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return before_given_date
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def getResult(score,teamHome):
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x,y = score.split('-')
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@ -86,23 +54,6 @@ def getResult(score,teamHome):
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else:
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return "loss"
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# def calculateAggression(matches, team):
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# aggression = 0
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# for index, row in matches.iterrows():
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# if team == row['home_team']:
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# yellow_cards = row['home_yellow_cards']
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# red_cards = row['home_red_cards']
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# else:
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# yellow_cards = row['away_yellow_cards']
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# red_cards = row['away_red_cards']
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# aggression_result = calculateFuzzyAggression(yellow_cards, red_cards)
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# #print(aggression_result['aggression'])
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# aggression = aggression + aggression_result['aggression']
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# if matches.shape[0] != 0:
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# aggression_avg = aggression / matches.shape[0]
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# else:
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# aggression_avg = 0
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# return aggression_avg
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def calculatePoints(matches, team):
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points = 0
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@ -139,18 +90,3 @@ def calculateGoalDifference(matches, team):
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else:
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goal_diff = goal_diff + (y-x)
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return goal_diff
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def calculateColumn(matches, team, column_name):
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result = 0
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for index, row in matches.iterrows():
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if team == row['home_team']:
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column = row[column_name]
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else:
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column = row[column_name]
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result = result + column
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if matches.shape[0] != 0:
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result_avg = result / matches.shape[0]
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else:
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result_avg = 0
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return result_avg
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1032
df_parts.csv
1032
df_parts.csv
File diff suppressed because it is too large
Load Diff
222
fuzzy.py
222
fuzzy.py
@ -1,222 +0,0 @@
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from simpful import *
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from data_filters import *
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import pandas as pd
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FS = FuzzySystem()
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# Dominacja OK
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# Jakość strzałów - Witek
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# Agresesywnosc (zolte + czerwone kartki) - Wojtek
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# odbiory i wslizgi (xDef) - Michał, ekspert od xDef
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# statystyki z calego sezonu - Wojtek OK
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# 5 ostatnich spotkan miedzy druzynami - Witek
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def categorizeFuzzyPasses(passes,possession):
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FS.set_crisp_output_value("low", 0.0)
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FS.set_crisp_output_value("average", 0.5)
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FS.set_crisp_output_value("high", 1.0)
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Pass1 = TriangleFuzzySet(300,300,600, term="low")
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Pass2 = TriangleFuzzySet(110,440,770, term="average")
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Pass3 = TriangleFuzzySet(200,600,600, term="high")
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FS.add_linguistic_variable("passes", LinguisticVariable([Pass1, Pass2, Pass3], universe_of_discourse=[0,1000]))
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Poss1 = TriangleFuzzySet(30,30,50, term="low")
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Poss2 = TriangleFuzzySet(35,50,65, term="average")
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Poss3 = TriangleFuzzySet(50,70,70, term="high")
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FS.add_linguistic_variable("possession", LinguisticVariable([Poss1, Poss2, Poss3], universe_of_discourse=[0,100]))
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#Pass_domination1 = TriangleFuzzySet(2,2,6, term="low")
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#Pass_domination2 = TriangleFuzzySet(3,5,7, term="average")
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#Pass_domination3 = TriangleFuzzySet(4,8,8, term="high")
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#FS.add_linguistic_variable("passes_domination", LinguisticVariable([Pass_domination1, Pass_domination2, Pass_domination3], universe_of_discourse=[0,10]))
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FS.add_rules([
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"IF (passes IS low) AND (possession IS low) THEN (pass_domination IS low)",
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"IF (passes IS high) AND (possession IS high) THEN (pass_domination IS high)",
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"IF (passes IS average) AND (possession IS average) THEN (pass_domination IS average)",
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"IF (passes IS low) AND (possession IS high) THEN (pass_domination IS average)",
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"IF (passes IS high ) AND (possession IS low) THEN (pass_domination IS average)",
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"IF (passes IS average) AND (possession IS high) THEN (pass_domination IS high)",
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"IF (passes IS high) AND (possession IS average) THEN (pass_domination IS high)",
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"IF (passes IS low) AND (possession IS average) THEN (pass_domination IS low)",
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"IF (passes IS average) AND (possession IS low) THEN (pass_domination IS average)"
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])
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FS.set_variable("passes", passes)
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FS.set_variable("possession", possession)
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pass_domination = FS.inference()
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return pass_domination['pass_domination']
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def categorizeFuzzyDefence(tackles,clearances):
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FS.set_crisp_output_value("low", 0.0)
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FS.set_crisp_output_value("average", 0.5)
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FS.set_crisp_output_value("high", 1.0)
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Tackle1 = TriangleFuzzySet(12,12,24, term="low")
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Tackle2 = TriangleFuzzySet(6,18,30, term="average")
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Tackle3 = TriangleFuzzySet(12,24,24, term="high")
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FS.add_linguistic_variable("tackles", LinguisticVariable([Tackle1, Tackle2, Tackle3], universe_of_discourse=[0,80]))
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Clear1 = TriangleFuzzySet(12,12,36, term="low")
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Clear2 = TriangleFuzzySet(9,27,45, term="average")
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Clear3 = TriangleFuzzySet(18,42,42, term="high")
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FS.add_linguistic_variable("clearances", LinguisticVariable([Clear1, Clear2, Clear3], universe_of_discourse=[0,80]))
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FS.add_rules([
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"IF (tackles IS low) AND (clearances IS low) THEN (defence_actions IS low)",
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"IF (tackles IS high) AND (clearances IS high) THEN (defence_actions IS high)",
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"IF (tackles IS average) AND (clearances IS average) THEN (defence_actions IS average)",
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"IF (tackles IS low) AND (clearances IS high) THEN (defence_actions IS average)",
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"IF (tackles IS high ) AND (clearances IS low) THEN (defence_actions IS average)",
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"IF (tackles IS average) AND (clearances IS high) THEN (defence_actions IS high)",
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"IF (tackles IS high) AND (clearances IS average) THEN (defence_actions IS high)",
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"IF (tackles IS low) AND (clearances IS average) THEN (defence_actions IS low)",
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"IF (tackles IS average) AND (clearances IS low) THEN (defence_actions IS average)"
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])
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FS.set_variable("tackles", tackles)
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FS.set_variable("clearances", clearances)
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defence_actions = FS.inference()
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return defence_actions['defence_actions']
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def categorizeFuzzyShots(shots_overall, shots_on_target):
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FS.set_crisp_output_value("low", 0.0)
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FS.set_crisp_output_value("average", 0.5)
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FS.set_crisp_output_value("high", 1.0)
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Shot_ov1 = TriangleFuzzySet(3,3,12, term="low") #pozmieniać przedziały (nakładają się)
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Shot_ov2 = TriangleFuzzySet(2,12,22, term="average")
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Shot_ov3 = TriangleFuzzySet(6,25,25, term="high")
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FS.add_linguistic_variable("shots_overall", LinguisticVariable([Shot_ov1, Shot_ov2, Shot_ov3], universe_of_discourse=[0,35]))
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Shot_ont1 = TriangleFuzzySet(1,1,6, term="low")
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Shot_ont2 = TriangleFuzzySet(2,5,8, term="average")
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Shot_ont3 = TriangleFuzzySet(3,10,10, term="high")
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FS.add_linguistic_variable("shots_on_target", LinguisticVariable([Shot_ont1, Shot_ont2, Shot_ont3], universe_of_discourse=[0,15]))
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#Qual_of_shots1 = TriangleFuzzySet(0,0,0.3, term="low")
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#Qual_of_shots2 = TriangleFuzzySet(0.2,0.5,0.8, term="medium")
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#Qual_of_shots3 = TriangleFuzzySet(0.7,1,1, term="high")
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#FS.add_linguistic_variable("expected_goals", LinguisticVariable([Qual_of_shots1, Qual_of_shots2, Qual_of_shots3], universe_of_discourse=[0,1]))
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FS.add_rules([
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"IF (shots_overall IS low) AND (shots_on_target IS low) THEN (quality_of_shots IS low)",
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"IF (shots_overall IS high) AND (shots_on_target IS high) THEN (quality_of_shots IS high)",
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"IF (shots_overall IS average) AND (shots_on_target IS average) THEN (quality_of_shots IS average)",
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"IF (shots_overall IS low) AND (shots_on_target IS high) THEN (quality_of_shots IS average)",
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"IF (shots_overall IS high ) AND (shots_on_target IS low) THEN (quality_of_shots IS low)",
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"IF (shots_overall IS average) AND (shots_on_target IS high) THEN (quality_of_shots IS high)",
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"IF (shots_overall IS high) AND (shots_on_target IS average) THEN (quality_of_shots IS average)",
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"IF (shots_overall IS low) AND (shots_on_target IS average) THEN (quality_of_shots IS average)",
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"IF (shots_overall IS average) AND (shots_on_target IS low) THEN (quality_of_shots IS low)"
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])
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FS.set_variable("shots_overall", shots_overall)
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FS.set_variable("shots_on_target", shots_on_target)
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quality_of_shots = FS.inference()
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return quality_of_shots['quality_of_shots']
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def calculateFuzzyAggression(yellow_cards, red_cards):
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FS.set_crisp_output_value("low", 0.0)
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FS.set_crisp_output_value("average", 0.5)
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FS.set_crisp_output_value("high", 1.0)
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Yellow_cards1 = TriangleFuzzySet(0, 2, 4, term="low")
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Yellow_cards2 = TriangleFuzzySet(1, 3, 5, term="average")
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Yellow_cards3 = TriangleFuzzySet(2, 4, 4, term="high")
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FS.add_linguistic_variable("yellow_cards", LinguisticVariable([Yellow_cards1, Yellow_cards2, Yellow_cards3], universe_of_discourse=[0, 10]))
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Red_cards1 = TriangleFuzzySet(0, 0, 1, term="low")
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Red_cards2 = TriangleFuzzySet(0, 1, 2, term="average")
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Red_cards3 = TriangleFuzzySet(1, 2, 2, term="high")
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FS.add_linguistic_variable("red_cards", LinguisticVariable([Red_cards1, Red_cards2, Red_cards3], universe_of_discourse=[0, 4]))
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# Pass_domination1 = TriangleFuzzySet(2,2,6, term="low")
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# Pass_domination2 = TriangleFuzzySet(3,5,7, term="average")
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# Pass_domination3 = TriangleFuzzySet(4,8,8, term="high")
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# FS.add_linguistic_variable("passes_domination", LinguisticVariable([Pass_domination1, Pass_domination2, Pass_domination3], universe_of_discourse=[0,10]))
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FS.add_rules([
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"IF (yellow_cards IS low) AND (red_cards IS low) THEN (aggression IS low)",
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"IF (yellow_cards IS high) AND (red_cards IS high) THEN (aggression IS high)",
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"IF (yellow_cards IS average) AND (red_cards IS average) THEN (aggression IS average)",
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"IF (yellow_cards IS low) AND (red_cards IS high) THEN (aggression IS high)",
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"IF (yellow_cards IS high ) AND (red_cards IS low) THEN (aggression IS high)",
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"IF (yellow_cards IS average) AND (red_cards IS high) THEN (aggression IS high)",
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"IF (yellow_cards IS high) AND (red_cards IS average) THEN (aggression IS high)",
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"IF (yellow_cards IS low) AND (red_cards IS average) THEN (aggression IS average)",
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"IF (yellow_cards IS average) AND (red_cards IS low) THEN (aggression IS average)"
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])
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FS.set_variable("yellow_cards", yellow_cards)
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FS.set_variable("red_cards", red_cards)
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aggression = FS.inference()
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return aggression['aggression']
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203
main.py
203
main.py
@ -2,13 +2,13 @@ import pandas as pd
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from simpful import *
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from rules import *
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from data_filters import *
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from fuzzy import *
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from sklearn.ensemble import RandomForestClassifier
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from sklearn.model_selection import train_test_split
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from sklearn.metrics import accuracy_score
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from sklearn.preprocessing import LabelEncoder
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from sklearn.metrics import classification_report
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from sklearn.ensemble import GradientBoostingClassifier
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# Ostatnie 5 spotkań
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@ -22,25 +22,18 @@ from sklearn.ensemble import GradientBoostingClassifier
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if __name__ == "__main__":
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df = pd.read_csv('df_parts.csv')
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'''
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df = pd.read_csv('df_full_premierleague.csv')
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result = last5Matches('10/11', 'Stoke City', '2010-10-02', df)[0]
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result = last5Matches('10/11', 'Stoke City', '2010-10-02', df)
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#print(result.to_markdown())
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#print(result)
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result = last5Matches('10/11', 'Blackburn Rovers', '2010-10-02', df)[0]
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result = last5Matches('10/11', 'Blackburn Rovers', '2010-10-02', df)
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#print(result.to_markdown())
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#print(result)
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print(calculatePoints(result,'Blackburn Rovers'))
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print(calculateGoalDifference(result, 'Blackburn Rovers'))
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# df = generateTrainingData(df)
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# df = add_column(df, categorize_passes, "c_away_passes", "away_passes")
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# df = add_column(df, categorize_passes, "c_home_passes", "home_passes")
|
||||
@ -51,160 +44,19 @@ if __name__ == "__main__":
|
||||
# df = add_column(df, categorize_shots, "c_away_shots", "away_shots")
|
||||
# df = add_column(df, categorize_shots, "c_home_shots", "home_shots")
|
||||
# print(df.columns)
|
||||
###############################################################################################
|
||||
# df = add_column(df, getColumnMethod(df, True, 'home_yellow_cards', seasonMatches), "c_home_yellow_cards_s")
|
||||
# df = add_column(df, getColumnMethod(df, True, 'away_yellow_cards', seasonMatches), "c_away_yellow_cards_s")
|
||||
# df = add_column(df, getColumnMethod(df, True, 'home_red_cards', seasonMatches), "c_home_red_cards_s")
|
||||
# df = add_column(df, getColumnMethod(df, True, 'away_red_cards', seasonMatches), "c_away_red_cards_s")
|
||||
df = df.sort_values(by='date', ascending=False)
|
||||
|
||||
df = add_column(df, getColumnMethod(df, True, 'home_yellow_cards', last5Matches), "c_home_yellow_cards_5m")
|
||||
df = add_column(df, getColumnMethod(df, False, 'away_yellow_cards', last5Matches), "c_away_yellow_cards_5m")
|
||||
df = add_column(df, getColumnMethod(df, True, 'home_red_cards', last5Matches), "c_home_red_cards_5m")
|
||||
df = add_column(df, getColumnMethod(df, False, 'away_red_cards', last5Matches), "c_away_red_cards_5m")
|
||||
|
||||
df = add_column(df, getColumnMethod5Btw(df, True, 'home_yellow_cards', last5MatchesBtwTeams),
|
||||
"c_home_yellow_cards_5btw")
|
||||
df = add_column(df, getColumnMethod5Btw(df, False, 'away_yellow_cards', last5MatchesBtwTeams),
|
||||
"c_away_yellow_cards_5btw")
|
||||
df = add_column(df, getColumnMethod5Btw(df, True, 'home_red_cards', last5MatchesBtwTeams), "c_home_red_cards_5btw")
|
||||
df = add_column(df, getColumnMethod5Btw(df, False, 'away_red_cards', last5MatchesBtwTeams), "c_away_red_cards_5btw")
|
||||
|
||||
|
||||
|
||||
###################################################################################################################
|
||||
# df = add_column(df, getColumnMethod(df, True, 'home_shots', seasonMatches), "c_home_shots_s")
|
||||
# df = add_column(df, getColumnMethod(df, True, 'away_shots', seasonMatches), "c_away_shots_s")
|
||||
# df = add_column(df, getColumnMethod(df, True, 'home_shots_on_target', seasonMatches), "c_home_shots_on_target_s")
|
||||
# df = add_column(df, getColumnMethod(df, True, 'away_shots_on_target', seasonMatches), "c_away_shots_on_target_s")
|
||||
|
||||
df = add_column(df, getColumnMethod(df, True, 'home_shots', last5Matches), "c_home_shots_5m")
|
||||
df = add_column(df, getColumnMethod(df, False, 'away_shots', last5Matches), "c_away_shots_5m")
|
||||
df = add_column(df, getColumnMethod(df, True, 'home_shots_on_target', last5Matches), "c_home_shots_on_target_5m")
|
||||
df = add_column(df, getColumnMethod(df, False, 'away_shots_on_target', last5Matches), "c_away_shots_on_target_5m")
|
||||
|
||||
df = add_column(df, getColumnMethod5Btw(df, True, 'home_shots', last5MatchesBtwTeams), "c_home_shots")
|
||||
df = add_column(df, getColumnMethod5Btw(df, False, 'away_shots', last5MatchesBtwTeams), "c_away_shots")
|
||||
df = add_column(df, getColumnMethod5Btw(df, True, 'home_shots_on_target', last5MatchesBtwTeams),
|
||||
"c_home_shots_on_target_5btw")
|
||||
df = add_column(df, getColumnMethod5Btw(df, False, 'away_shots_on_target', last5MatchesBtwTeams),
|
||||
"c_away_shots_on_target_5btw")
|
||||
|
||||
|
||||
###################################################################################################################################
|
||||
# df = add_column(df, getColumnMethod(df, True, 'home_tackles', seasonMatches), "c_home_tackles_s")
|
||||
# df = add_column(df, getColumnMethod(df, True, 'away_tackles', seasonMatches), "c_away_tackles_s")
|
||||
# df = add_column(df, getColumnMethod(df, True, 'home_clearances', seasonMatches), "c_home_clearances_s")
|
||||
# df = add_column(df, getColumnMethod(df, True, 'away_clearances', seasonMatches), "c_away_clearances_s")
|
||||
|
||||
df = add_column(df, getColumnMethod(df, True, 'home_tackles', last5Matches), "c_home_tackles_5m")
|
||||
df = add_column(df, getColumnMethod(df, False, 'away_tackles', last5Matches), "c_away_tackles_5m")
|
||||
df = add_column(df, getColumnMethod(df, True, 'home_clearances', last5Matches), "c_home_clearances_5m")
|
||||
df = add_column(df, getColumnMethod(df, False, 'away_clearances', last5Matches), "c_away_clearances_5m")
|
||||
|
||||
df = add_column(df, getColumnMethod5Btw(df, True, 'home_tackles', last5MatchesBtwTeams), "c_home_tackles_5btw")
|
||||
df = add_column(df, getColumnMethod5Btw(df, False, 'away_tackles', last5MatchesBtwTeams), "c_away_tackles_5btw")
|
||||
df = add_column(df, getColumnMethod5Btw(df, True, 'home_clearances', last5MatchesBtwTeams),
|
||||
"c_home_clearances_5btw")
|
||||
df = add_column(df, getColumnMethod5Btw(df, False, 'away_clearances', last5MatchesBtwTeams),
|
||||
"c_away_clearances_5btw")
|
||||
|
||||
|
||||
|
||||
####################################################################################################################################
|
||||
# df = add_column(df, getColumnMethod(df, True, 'home_passes', seasonMatches), "c_home_passes_s")
|
||||
# df = add_column(df, getColumnMethod(df, True, 'away_passes', seasonMatches), "c_away_passes_s")
|
||||
# df = add_column(df, getColumnMethod(df, True, 'home_possession', seasonMatches), "c_home_possession_s")
|
||||
# df = add_column(df, getColumnMethod(df, True, 'away_possession', seasonMatches), "c_away_possession_s")
|
||||
|
||||
df = add_column(df, getColumnMethod(df, True, 'home_passes', last5Matches), "c_home_passes_5m")
|
||||
df = add_column(df, getColumnMethod(df, False, 'away_passes', last5Matches), "c_away_passes_5m")
|
||||
df = add_column(df, getColumnMethod(df, True, 'home_possession', last5Matches), "c_home_possession_5m")
|
||||
df = add_column(df, getColumnMethod(df, False, 'away_possession', last5Matches), "c_away_possession_5m")
|
||||
|
||||
df = add_column(df, getColumnMethod5Btw(df, True, 'home_passes', last5MatchesBtwTeams), "c_home_passes_5btw")
|
||||
df = add_column(df, getColumnMethod5Btw(df, False, 'away_passes', last5MatchesBtwTeams), "c_away_passes_5btw")
|
||||
df = add_column(df, getColumnMethod5Btw(df, True, 'home_possession', last5MatchesBtwTeams),
|
||||
"c_home_possession_5btw")
|
||||
df = add_column(df, getColumnMethod5Btw(df, False, 'away_possession', last5MatchesBtwTeams),
|
||||
"c_away_possession_5btw")
|
||||
|
||||
# TU
|
||||
|
||||
|
||||
##########################################################################################################################################
|
||||
|
||||
df = add_column(df, get_method(df, True, categorize_points, last5Matches), "c_home_form_5m")
|
||||
df = add_column(df, get_method(df, False, categorize_points, last5Matches), "c_away_form_5m")
|
||||
|
||||
df = add_column(df, get_method(df, True, categorize_diff, seasonMatches), "c_home_diff_5m")
|
||||
df = add_column(df, get_method(df, False, categorize_diff, seasonMatches), "c_away_diff_5m")
|
||||
df = add_column(df, get_method(df, True, categorize_diff, last5Matches), "c_home_diff_5m")#categorize_diff
|
||||
df = add_column(df, get_method(df, False, categorize_diff,last5Matches), "c_away_diff_5m")
|
||||
|
||||
df = add_column(df, get_method(df, True, categorize_points_Btw, last5MatchesBtwTeams), "c_home_form_5btw")
|
||||
df = add_column(df, get_method(df, False, categorize_points_Btw, last5MatchesBtwTeams), "c_away_form_5btw")
|
||||
df = add_column(df, get_method(df, True, categorize_points, seasonMatches), "c_home_form_season")
|
||||
df = add_column(df, get_method(df, False, categorize_points, seasonMatches), "c_away_form_season")
|
||||
|
||||
df = add_column(df, get_method(df, True, categorize_diff_Btw, last5MatchesBtwTeams), "c_home_diff_5btw")
|
||||
df = add_column(df, get_method(df, False, categorize_diff_Btw, last5MatchesBtwTeams), "c_away_diff_5btw")
|
||||
df = add_column(df, get_method(df, True, categorize_diff, seasonMatches), "c_home_diff_season")#categorize_diff
|
||||
df = add_column(df, get_method(df, False, categorize_diff,seasonMatches), "c_away_diff_season")
|
||||
|
||||
df = add_column(df, get_method(df, True, categorize_points, seasonMatches), "c_home_form_5s")
|
||||
df = add_column(df, get_method(df, False, categorize_points, seasonMatches), "c_away_form_5s")
|
||||
|
||||
df = add_column(df, get_method(df, True, categorize_diff, seasonMatches), "c_home_diff_5s")
|
||||
df = add_column(df, get_method(df, False, categorize_diff, seasonMatches), "c_away_diff_5s")
|
||||
|
||||
df.to_csv('df.csv', index=False)
|
||||
#TU sie zapisuje zbior
|
||||
|
||||
part_size = 50
|
||||
for part in split_to_parts(df, part_size):
|
||||
|
||||
|
||||
part = add_column(part,
|
||||
getFuzzyMethod(part, calculateFuzzyAggression, True, "c_home_yellow_cards_5m", "c_home_red_cards_5m"),
|
||||
"c_home_aggression_5m")
|
||||
part = add_column(part, getFuzzyMethod(part, calculateFuzzyAggression, False, "c_away_yellow_cards_5m",
|
||||
"c_away_red_cards_5m"), "c_away_aggression_5m")
|
||||
|
||||
part = add_column(part, getFuzzyMethod(part, calculateFuzzyAggression, True, "c_home_yellow_cards_5btw",
|
||||
"c_home_red_cards_5btw"), "c_home_aggression_5btw")
|
||||
part = add_column(part, getFuzzyMethod(part, calculateFuzzyAggression, False, "c_away_yellow_cards_5btw",
|
||||
"c_away_red_cards_5btw"), "c_away_aggression_5btw")
|
||||
|
||||
part = add_column(part, getFuzzyMethod(part, categorizeFuzzyShots, True, "c_home_shots_5m", "c_home_shots_5m"),
|
||||
"c_home_shots_5m")
|
||||
part = add_column(part, getFuzzyMethod(part, categorizeFuzzyShots, False, "c_away_shots_5m", "c_away_shots_5m"),
|
||||
"c_away_shots_5m")
|
||||
|
||||
part = add_column(part, getFuzzyMethod(part, categorizeFuzzyShots, True, "c_home_shots_on_target_5btw",
|
||||
"c_home_shots_on_target_5btw"), "c_home_shots_5btw")
|
||||
part = add_column(part, getFuzzyMethod(part, categorizeFuzzyShots, False, "c_away_shots_on_target_5btw",
|
||||
"c_away_shots_on_target_5btw"), "c_away_shots_5btw")
|
||||
|
||||
part = add_column(part, getFuzzyMethod(part, categorizeFuzzyDefence, True, "c_home_tackles_5m", "c_home_clearances_5m"),
|
||||
"c_home_defence_5m")
|
||||
part = add_column(part, getFuzzyMethod(part, categorizeFuzzyDefence, False, "c_away_tackles_5m", "c_away_clearances_5m"),
|
||||
"c_away_defence_5m")
|
||||
|
||||
part = add_column(part,
|
||||
getFuzzyMethod(part, categorizeFuzzyDefence, True, "c_home_tackles_5btw", "c_home_clearances_5btw"),
|
||||
"c_home_defence_5btw")
|
||||
part = add_column(part,
|
||||
getFuzzyMethod(part, categorizeFuzzyDefence, False, "c_away_tackles_5btw", "c_away_clearances_5btw"),
|
||||
"c_away_defence_5btw")
|
||||
part = add_column(part, getFuzzyMethod(part, categorizeFuzzyPasses, True, "c_home_passes_5m", "c_home_possession_5m"),
|
||||
"c_home_passing_5m")
|
||||
part = add_column(part, getFuzzyMethod(part, categorizeFuzzyPasses, False, "c_away_passes_5m", "c_away_possession_5m"),
|
||||
"c_away_passing_5m")
|
||||
|
||||
part = add_column(part, getFuzzyMethod(part, categorizeFuzzyPasses, True, "c_home_passes_5btw", "c_home_possession_5btw"),
|
||||
"c_home_passing_5btw")
|
||||
part = add_column(part,
|
||||
getFuzzyMethod(part, categorizeFuzzyPasses, False, "c_away_passes_5btw", "c_away_possession_5btw"),
|
||||
"c_away_passing_5btw")
|
||||
|
||||
|
||||
save_to_csv("df_parts", part)
|
||||
'''
|
||||
df = generateFuzzyLogicData(df)
|
||||
|
||||
label_encoder = LabelEncoder()
|
||||
@ -216,12 +68,9 @@ if __name__ == "__main__":
|
||||
df[['home_team', 'away_team']] = temp.unstack()
|
||||
X = df.drop(['result_full', 'date', 'c_home_result', 'c_away_result'], axis=1)
|
||||
y = df['c_home_result']
|
||||
#y = label_encoder.fit_transform(df['c_home_result'])
|
||||
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
|
||||
|
||||
model = RandomForestClassifier(n_estimators=500, random_state=42)
|
||||
#model = GradientBoostingClassifier(learning_rate=0.1, n_estimators=100, random_state = 42)
|
||||
|
||||
model = RandomForestClassifier(n_estimators=100, random_state=42)
|
||||
model.fit(X_train, y_train)
|
||||
|
||||
y_pred = model.predict(X_test)
|
||||
@ -233,28 +82,8 @@ if __name__ == "__main__":
|
||||
print(f'Dokładność modelu: {accuracy}')
|
||||
print(classification_report(y_test, y_pred))
|
||||
|
||||
#print(model.feature_importances_)
|
||||
result = last5Matches('10/11', 'Manchester United', '2010-12-16', df)
|
||||
print(calculatePoints(result,'Manchester United'))
|
||||
print(calculateGoalDifference(result, 'Manchester United'))
|
||||
|
||||
|
||||
#print(categorize_fuzzy_passes(450,50))
|
||||
|
||||
#df.to_csv('df.csv', index=False)
|
||||
|
||||
|
||||
# df = add_column(df, get_method(df, True, categorize_aggression, last5Matches), "c_home_aggression_5m")#categorize_diff
|
||||
# df = add_column(df, get_method(df, False, categorize_aggression,last5Matches), "c_away_aggression_5m")
|
||||
# df = add_column(df, get_method(df, True, categorize_points, seasonMatches), "c_home_form_season")
|
||||
# df = add_column(df, get_method(df, False, categorize_points, seasonMatches), "c_away_form_season")
|
||||
|
||||
#df = add_column(df, get_method(df, True, categorize_diff, seasonMatches), "c_home_diff_season")#categorize_diff
|
||||
# df = add_column(df, get_method(df, False, categorize_diff,seasonMatches), "c_away_diff_season")
|
||||
|
||||
# df = add_column(df, get_method(df, True, categorize_aggression, seasonMatches), "c_home_aggression_season")#categorize_diff
|
||||
# df = add_column(df, get_method(df, False, categorize_aggression,seasonMatches), "c_away_aggression_season")
|
||||
|
||||
|
||||
#df = add_column(df, get_method(df, True, categorize_points, last5MatchesBtwTeams), "c_home_form_5btw")
|
||||
#df = add_column(df, get_method(df, False, categorize_points, last5MatchesBtwTeams), "c_away_form_5btw")
|
||||
|
||||
#df = add_column(df, get_method(df, True, categorize_diff, last5MatchesBtwTeams), "c_home_diff_5btw")#categorize_diff
|
||||
#df = add_column(df, get_method(df, False, categorize_diff,last5MatchesBtwTeams), "c_away_diff_5btw")
|
||||
print(categorize_fuzzy_passes(450,50))
|
||||
220
rules.py
220
rules.py
@ -1,6 +1,121 @@
|
||||
import simpful
|
||||
from data_filters import *
|
||||
import pandas as pd
|
||||
|
||||
FS = FuzzySystem()
|
||||
|
||||
# Dominacja OK
|
||||
# Jakość strzałów - Witek
|
||||
# Agresesywnosc (zolte + czerwone kartki) - Wojtek
|
||||
# odbiory i wslizgi (xDef) - Michał, ekspert od xDef
|
||||
# statystyki z calego sezonu - Wojtek OK
|
||||
# 5 ostatnich spotkan miedzy druzynami - Witek
|
||||
def categorize_fuzzy_passes(passes,possession):
|
||||
|
||||
|
||||
FS.set_crisp_output_value("low", 0.0)
|
||||
FS.set_crisp_output_value("average", 0.5)
|
||||
FS.set_crisp_output_value("high", 1.0)
|
||||
|
||||
Pass1 = TriangleFuzzySet(300,300,500, term="low")
|
||||
Pass2 = TriangleFuzzySet(300,450,600, term="average")
|
||||
Pass3 = TriangleFuzzySet(400,600,600, term="high")
|
||||
|
||||
FS.add_linguistic_variable("passes", LinguisticVariable([Pass1, Pass2, Pass3], universe_of_discourse=[0,1000]))
|
||||
|
||||
Poss1 = TriangleFuzzySet(30,30,45, term="low")
|
||||
Poss2 = TriangleFuzzySet(40,50,60, term="average")
|
||||
Poss3 = TriangleFuzzySet(55,70,70, term="high")
|
||||
|
||||
FS.add_linguistic_variable("possession", LinguisticVariable([Poss1, Poss2, Poss3], universe_of_discourse=[0,100]))
|
||||
|
||||
|
||||
#Pass_domination1 = TriangleFuzzySet(2,2,6, term="low")
|
||||
#Pass_domination2 = TriangleFuzzySet(3,5,7, term="average")
|
||||
#Pass_domination3 = TriangleFuzzySet(4,8,8, term="high")
|
||||
|
||||
#FS.add_linguistic_variable("passes_domination", LinguisticVariable([Pass_domination1, Pass_domination2, Pass_domination3], universe_of_discourse=[0,10]))
|
||||
|
||||
|
||||
FS.add_rules([
|
||||
|
||||
"IF (passes IS low) AND (possession IS low) THEN (pass_domination IS low)",
|
||||
|
||||
"IF (passes IS high) AND (possession IS high) THEN (pass_domination IS high)",
|
||||
|
||||
"IF (passes IS average) AND (possession IS average) THEN (pass_domination IS average)",
|
||||
|
||||
"IF (passes IS low) AND (possession IS high) THEN (pass_domination IS average)",
|
||||
|
||||
"IF (passes IS high ) AND (possession IS low) THEN (pass_domination IS average)",
|
||||
|
||||
"IF (passes IS average) AND (possession IS high) THEN (pass_domination IS high)",
|
||||
|
||||
"IF (passes IS high) AND (possession IS average) THEN (pass_domination IS high)",
|
||||
|
||||
"IF (passes IS low) AND (possession IS average) THEN (pass_domination IS low)",
|
||||
|
||||
"IF (passes IS average) AND (possession IS low) THEN (pass_domination IS average)"
|
||||
])
|
||||
|
||||
FS.set_variable("passes", passes)
|
||||
|
||||
FS.set_variable("possession", possession)
|
||||
|
||||
pass_domination = FS.inference()
|
||||
|
||||
return pass_domination
|
||||
|
||||
def categorize_fuzzy_shots(shots_overall, shots_on_target):
|
||||
|
||||
FS.set_crisp_output_value("low", 0.0)
|
||||
FS.set_crisp_output_value("average", 0.5)
|
||||
FS.set_crisp_output_value("high", 1.0)
|
||||
|
||||
Shot_ov1 = TriangleFuzzySet(0,0,5, term="low") #pozmieniać przedziały (nakładają się)
|
||||
Shot_ov2 = TriangleFuzzySet(5,10,15, term="medium")
|
||||
Shot_ov3 = TriangleFuzzySet(15,25,25, term="high")
|
||||
|
||||
FS.add_linguistic_variable("shots_overall", LinguisticVariable([Shot_ov1, Shot_ov2, Shot_ov3], universe_of_discourse=[0,35]))
|
||||
|
||||
Shot_ont1 = TriangleFuzzySet(0,0,2, term="low")
|
||||
Shot_ont2 = TriangleFuzzySet(2,4,6, term="medium")
|
||||
Shot_ont3 = TriangleFuzzySet(6,10,10, term="high")
|
||||
|
||||
FS.add_linguistic_variable("shots_on_target", LinguisticVariable([Shot_ont1, Shot_ont2, Shot_ont3], universe_of_discourse=[0,15]))
|
||||
|
||||
|
||||
#Qual_of_shots1 = TriangleFuzzySet(0,0,0.3, term="low")
|
||||
#Qual_of_shots2 = TriangleFuzzySet(0.2,0.5,0.8, term="medium")
|
||||
#Qual_of_shots3 = TriangleFuzzySet(0.7,1,1, term="high")
|
||||
|
||||
#FS.add_linguistic_variable("expected_goals", LinguisticVariable([Qual_of_shots1, Qual_of_shots2, Qual_of_shots3], universe_of_discourse=[0,1]))
|
||||
|
||||
|
||||
FS.add_rules([
|
||||
|
||||
"IF (shots_overall IS low) AND (shots_on_target IS low) THEN (quality_of_shots IS low)",
|
||||
|
||||
"IF (shots_overall IS high) AND (shots_on_target IS high) THEN (quality_of_shots IS high)",
|
||||
|
||||
"IF (shots_overall IS average) AND (shots_on_target IS average) THEN (quality_of_shots IS average)",
|
||||
|
||||
"IF (shots_overall IS low) AND (shots_on_target IS high) THEN (quality_of_shots IS high)",
|
||||
|
||||
"IF (shots_overall IS high ) AND (shots_on_target IS low) THEN (quality_of_shots IS low)",
|
||||
|
||||
"IF (shots_overall IS average) AND (possession IS high) THEN (quality_of_shots IS high)",
|
||||
|
||||
"IF (passes IS high) AND (possession IS average) THEN (quality_of_shots IS high)",
|
||||
|
||||
"IF (passes IS low) AND (possession IS average) THEN (quality_of_shots IS low)",
|
||||
|
||||
"IF (passes IS average) AND (possession IS low) THEN (quality_of_shots IS average)"
|
||||
|
||||
])
|
||||
|
||||
|
||||
|
||||
|
||||
def categorize_shots(shots):
|
||||
if shots >= 12:
|
||||
@ -28,10 +143,10 @@ def categorize_possesion(shots):
|
||||
|
||||
def categorize_points(data, row, teamHome, matches_type):
|
||||
if teamHome:
|
||||
data_5 = matches_type(row['season'], row['home_team'], row['date'], data)[0]
|
||||
data_5 = matches_type(row['season'], row['home_team'], row['date'], data)
|
||||
points = calculatePoints(data_5,row['home_team'])
|
||||
else:
|
||||
data_5 = matches_type(row['season'], row['away_team'], row['date'], data)[0]
|
||||
data_5 = matches_type(row['season'], row['away_team'], row['date'], data)
|
||||
points = calculatePoints(data_5,row['away_team'])
|
||||
if points <=1:
|
||||
return 0
|
||||
@ -40,30 +155,12 @@ def categorize_points(data, row, teamHome, matches_type):
|
||||
else:
|
||||
return 1
|
||||
|
||||
def categorize_points_Btw(data, row, teamHome, matches_type):
|
||||
if teamHome:
|
||||
data_5 = matches_type(row['home_team'], row['away_team'], row['date'], data)[0]
|
||||
points = calculatePoints(data_5,row['home_team'])
|
||||
else:
|
||||
data_5 = matches_type(row['home_team'], row['away_team'], row['date'], data)[0]
|
||||
points = calculatePoints(data_5,row['away_team'])
|
||||
if points <=1:
|
||||
return 0
|
||||
elif points >=2:
|
||||
return 2
|
||||
else:
|
||||
return 1
|
||||
|
||||
|
||||
|
||||
|
||||
def get_method(data, home_away, method, matches_type):
|
||||
values = []
|
||||
for index, row in data.iterrows():
|
||||
values.append(method(data, row, home_away, matches_type))
|
||||
return values
|
||||
|
||||
|
||||
def get_points_home(data):
|
||||
points = []
|
||||
for index, row in data.iterrows():
|
||||
@ -83,22 +180,10 @@ def get_points_away(data):
|
||||
|
||||
def categorize_diff(data, row, teamHome, matches_type):
|
||||
if teamHome:
|
||||
data_5 = matches_type(row['season'], row['home_team'], row['date'], data)[0]
|
||||
data_5 = matches_type(row['season'], row['home_team'], row['date'], data)
|
||||
diff = calculateGoalDifference(data_5,row['home_team'])
|
||||
else:
|
||||
data_5 = matches_type(row['season'], row['away_team'], row['date'], data)[0]
|
||||
diff = calculateGoalDifference(data_5,row['away_team'])
|
||||
if diff <=0:
|
||||
return 0
|
||||
else:
|
||||
return 1
|
||||
|
||||
def categorize_diff_Btw(data, row, teamHome, matches_type):
|
||||
if teamHome:
|
||||
data_5 = matches_type(row['home_team'], row['away_team'], row['date'], data)[0]
|
||||
diff = calculateGoalDifference(data_5,row['home_team'])
|
||||
else:
|
||||
data_5 = matches_type(row['home_team'], row['away_team'], row['date'], data)[0]
|
||||
data_5 = matches_type(row['season'], row['away_team'], row['date'], data)
|
||||
diff = calculateGoalDifference(data_5,row['away_team'])
|
||||
if diff <=0:
|
||||
return 0
|
||||
@ -106,30 +191,6 @@ def categorize_diff_Btw(data, row, teamHome, matches_type):
|
||||
return 1
|
||||
|
||||
|
||||
def categorize_diff(data, row, teamHome, matches_type):
|
||||
if teamHome:
|
||||
data_5 = matches_type(row['season'], row['home_team'], row['date'], data)[0]
|
||||
diff = calculateGoalDifference(data_5,row['home_team'])
|
||||
else:
|
||||
data_5 = matches_type(row['season'], row['away_team'], row['date'], data)[0]
|
||||
diff = calculateGoalDifference(data_5,row['away_team'])
|
||||
if diff <=0:
|
||||
return 0
|
||||
else:
|
||||
return 1
|
||||
|
||||
# def categorize_aggression(data, row, teamHome, matches_type):
|
||||
# if teamHome:
|
||||
# data_5 = matches_type(row['season'], row['home_team'], row['date'], data)
|
||||
# diff = calculateAggression(data_5,row['home_team'])
|
||||
# else:
|
||||
# data_5 = matches_type(row['season'], row['away_team'], row['date'], data)
|
||||
# diff = calculateAggression(data_5,row['away_team'])
|
||||
# return diff
|
||||
# # if diff <=0:
|
||||
# # return 0
|
||||
# # else:
|
||||
# # return 1
|
||||
def get_diff_home(data):
|
||||
points = []
|
||||
for index, row in data.iterrows():
|
||||
@ -162,46 +223,3 @@ def get_result_list(df, home_team):
|
||||
for score in df['result_full']:
|
||||
results.append(getResult(score,home_team))
|
||||
return results
|
||||
|
||||
def getColumnMethod(data, home_away, column, matches_type):
|
||||
values = []
|
||||
for index, row in data.iterrows():
|
||||
values.append(getColumnByMatches(data, row, home_away, matches_type,column))
|
||||
return values
|
||||
|
||||
def getColumnMethod5Btw(data, home_away, column, matches_type):
|
||||
values = []
|
||||
for index, row in data.iterrows():
|
||||
values.append(getColumnByMatches5Btw(data, row, home_away, matches_type,column))
|
||||
return values
|
||||
|
||||
def getFuzzyMethod(data, method, home_away, frist_column, second_column):
|
||||
values = []
|
||||
for index, row in data.iterrows():
|
||||
values.append(getFuzzyByMatches(method, row, home_away, frist_column, second_column))
|
||||
return values
|
||||
|
||||
def getColumnByMatches(data, row, teamHome, matches_type, column):
|
||||
if teamHome:
|
||||
data_5, end = matches_type(row['season'], row['home_team'], row['date'], data)
|
||||
result = calculateColumn(data_5, row['home_team'], column)
|
||||
else:
|
||||
data_5, end = matches_type(row['season'], row['away_team'], row['date'], data)
|
||||
result = calculateColumn(data_5, row['away_team'], column)
|
||||
return result
|
||||
|
||||
def getColumnByMatches5Btw(data, row, teamHome, matches_type, column):
|
||||
if teamHome:
|
||||
data_5, end = last5MatchesBtwTeams(row['home_team'], row['away_team'], row['date'], data)
|
||||
result = calculateColumn(data_5, row['home_team'], column)
|
||||
else:
|
||||
data_5, end = matches_type(row['home_team'], row['away_team'], row['date'], data)
|
||||
result = calculateColumn(data_5, row['away_team'], column)
|
||||
return result
|
||||
|
||||
def getFuzzyByMatches(method, row, teamHome, frist_column, second_column):
|
||||
if teamHome:
|
||||
result = method(row[frist_column], row[second_column])
|
||||
else:
|
||||
result = method(row[frist_column], row[second_column])
|
||||
return result
|
||||
Loading…
Reference in New Issue
Block a user